Local minima represent a major problem for neural network learning procedures. In this article we present a new procedure, collective learning, that leads to improved global convergence. We have tested our procedure on several neural networks and on the multimodal functions proposed by De Jong and Rastrigin. In our tests we have reached a success ratio of 100 %. In addition we give a few remark...

A primary concern when using local search methods for CNF satis ability is how to get rid of local minimas. Among many other heuristics, Weighting by Morris (1993) and Selman and Kautz (1993) works overwhelmingly better than others (Cha and Iwama 1995). Weighting increases the weight of each clause which is unsatis ed at a local minima. This paper introduces a more sophisticated weighting strat...

In this paper an approach is presented to incorporate prob lem speci c knowledge into a genetic algorithm which is used to compute near optimum solutions to traveling salesman problems TSP The ap proach is based on using a tour construction heuristic for generating the initial population a tour improvement heuristic for nding local optima in a given TSP search space and new genetic operators fo...

It has recently been shown that local search is surprisingly good at nding satisfying assignments for certain classes of CNF formulas (Sel-man et al. 1992). In this paper we demonstrate that the power of local search for satissability testing can be further enhanced by employing a new strategy, called \mixed random walk", for escaping from local minima. We present a detailed comparison of this ...

Our domain of interest is polygonal (and polyhedral) approximation of point sets. Neither the order of data points nor the number of needed line segments (surface patches) are known. In particular, point sets can be obtained by laser range scanner mounted on a moving robot or given as edge pixels/voxels in digital images. Polygonal approximation of edge pixels can also be interpreted as groupin...

Capacitated covering models aim at covering the maximum amount of customers’ demand using a set of capacitated facilities. Based on the assumptions made in such models, there is a unique scenario to open a facility in which each facility has a pre-specified capacity and an operating budget. In this paper, we propose a generalization of the maximal covering location problem, in which facilities ...

Parameter estimation in ordinary differential equations, although applied and refined in various fields of the quantitative sciences, is still confronted with a variety of difficulties. One major challenge is finding the global optimum of a log-likelihood function that has several local optima, e.g. in oscillatory systems. In this publication, we introduce a formulation based on continuation of...

A stochastic global optimization method based on Multistart is presented. In this, the local search is conditionally applied with a probability that takes in account the topology of the objective function at the detail offered by the current status of exploration. As a result, the number of unnecessary local searches is drastically limited, yielding an efficient method. Results of its applicati...

We consider a system which has an observable randomly changing increasing parameter φ(t). The observation is either continuous or discrete on a time scale with step δ. System's output on [0,t] depends on φ via the following reward functional: ∫ − = t dx x H t A 0 , ))] ( ( [ ) ( φ ψ where ψ(·)is a known increasing function. The operation and observation process can be stopped for a preventive m...

[1] This study assesses near surface lapse rates and temperatures over the past decade at two heights from the Oklahoma Mesonet. A statistically significant change in lapse rate was detected of 0.21 ± 0.09 C (10 m) 1 per decade. The trend of nighttime lapse rate was about three times larger than the magnitude of trend of the daytime lapse rate. The lapse rate trends at the time of the daily max...